---
title: "Heart Disease"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    logo: logo.png
    source_code: embed
    social: menu
---

```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(plotly)
library(knitr)
library(DT)

df <- read_csv('Heart_Disease.csv')

# Create a ggplot object
p <- df %>% 
  mutate(Disease = factor(`pred-2class`)) %>% 
  ggplot()+ 
  geom_bar(mapping=aes(x=sex, fill=Disease), 
           position = 'fill')+
  labs(y='Proportion', fill='Heart Disease')

p1 <- df %>% 
  mutate(Disease = factor(`pred-2class`)) %>% 
  ggplot()+ 
  geom_density(mapping=aes(x=age, color=Disease))+
  facet_wrap(~thal)
```

{.sidebar}
=======================================================================

### 1. Heart Disease

Heart disease is one of the most prevalent causes of death around the world. There are many factors that are involved in whether someone is likely to have heart disease or not.

### 2. Flexdashboard and Plotly

This interactive uses `flexdashboard` and `plotly` to visualize the data. 

Main Tab 1
=======================================================================

Column {data-width=500, .tabset}
-----------------------------------------------------------------------

### Column Tab 1

```{r}
df
```


### Column Tab 2

```{r}
kable(df)
```


### Column Tab 3

```{r}
datatable(df, options = list(
  pageLength = 25
))
```


Column {data-width=500}
-----------------------------------------------------------------------

### Row 1

```{r}
p
```

### Row 2

```{r}
ggplotly(p)
```


Main Tab 2
=======================================================================

Column {data-width=500}
-----------------------------------------------------------------------

#### 1. Plotly for R

Plotly is an R package for creating interactive web-based graphs via plotly's JavaScript graphing library, plotly.js.

The plotly R package serializes ggplot2 figures into Plotly's universal graph JSON. plotly::ggplotly will crawl the ggplot2 figure, extract and translate all of the attributes of the ggplot2 figure into JSON (the colors, the axes, the chart type, etc), and draw the graph with plotly.js. Furthermore, you have the option of manipulating the Plotly object with the style function.


#### 2. Cutomizing the Layout

Since the ggplotly() function returns a plotly object, we can manipulate that object in the same way that we would manipulate any other plotly object. A simple and useful application of this is to specify interaction modes, like plotly.js' layout.dragmode for specifying the mode of click+drag events.


#### 3. Example

```{r, echo=TRUE, eval=TRUE}
library(plotly)
df <- data.frame(x=c(1, 2, 3, 4), y=c(1, 5, 3, 5), group=c('A', 'A', 'B', 'B'))
p <- ggplot(data=df, aes(x=x, y=y, colour=group)) + geom_point()
ggplotly(p)
```



Column {data-width=500}
-----------------------------------------------------------------------

### Row 1

```{r}
p1
```

### Row 2

```{r}
ggplotly(p1)
```